{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checking whether there is an H2O instance running at http://localhost:54321"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " not found."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Attempting to start a local H2O server..."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Java Version: java version \"1.8.0_111\"; Java(TM) SE Runtime Environment (build 1.8.0_111-b14); Java HotSpot(TM) 64-Bit Server VM (build 25.111-b14, mixed mode)"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Starting server from /home/markc/H2O/h2o-3/h2o-py/h2o/backend/bin/h2o.jar"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Ice root: /tmp/tmpXaiTix"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  JVM stdout: /tmp/tmpXaiTix/h2o_markc_started_from_python.out"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  JVM stderr: /tmp/tmpXaiTix/h2o_markc_started_from_python.err"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Server is running at http://127.0.0.1:54321"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connecting to H2O server at http://127.0.0.1:54321.."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " successful."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"overflow:auto\"><table style=\"width:50%\"><tr><td>H2O cluster uptime:</td>\n",
       "<td>01 secs</td></tr>\n",
       "<tr><td>H2O cluster version:</td>\n",
       "<td>3.11.0.99999</td></tr>\n",
       "<tr><td>H2O cluster version age:</td>\n",
       "<td>1 day </td></tr>\n",
       "<tr><td>H2O cluster name:</td>\n",
       "<td>H2O_from_python_markc_erfi3v</td></tr>\n",
       "<tr><td>H2O cluster total nodes:</td>\n",
       "<td>1</td></tr>\n",
       "<tr><td>H2O cluster free memory:</td>\n",
       "<td>10.47 Gb</td></tr>\n",
       "<tr><td>H2O cluster total cores:</td>\n",
       "<td>12</td></tr>\n",
       "<tr><td>H2O cluster allowed cores:</td>\n",
       "<td>12</td></tr>\n",
       "<tr><td>H2O cluster status:</td>\n",
       "<td>accepting new members, healthy</td></tr>\n",
       "<tr><td>H2O connection url:</td>\n",
       "<td>http://127.0.0.1:54321</td></tr>\n",
       "<tr><td>H2O connection proxy:</td>\n",
       "<td>None</td></tr>\n",
       "<tr><td>Python version:</td>\n",
       "<td>2.7.12 final</td></tr></table></div>"
      ]
     },
     "output_type": "execute_result",
     "metadata": {}
    }
   ],
   "source": [
    "import h2o\n",
    "h2o.init()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Create Frame progress: |"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "██████████████████████████████████████████████████| 100%"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "df = h2o.create_frame(cols=256, rows=2, real_fraction=1.0, missing_fraction=0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.cumsum(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f8d81fd0990>"
      ]
     },
     "execution_count": 5,
     "output_type": "execute_result",
     "metadata": {}
    },
    {
     "data": {
      "image/png": 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EpJSyRggRBdQOjlcClu2/YgfHbLAUBpWxMdHy2s4kLiiOzUWbZ3oaKipnJMMfmh9//PEx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\noiiK4ocKg6IoiuLH/wPGqWJgCVEP5QAAAABJRU5ErkJggg==\n"
     },
     "output_type": "display_data",
     "text": [
      "<matplotlib.figure.Figure at 0x7f8d87a53ad0>"
     ],
     "metadata": {}
    }
   ],
   "source": [
    "df.transpose().as_data_frame(use_pandas=True).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = df.isax(num_words=10,max_cardinality=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tr><th>iSax_index                                       </th></tr>\n",
       "<tr><td>9^10_9^10_4^10_2^10_3^10_4^10_4^10_3^10_4^10_3^10</td></tr>\n",
       "<tr><td>5^10_6^10_8^10_5^10_3^10_4^10_4^10_4^10_4^10_3^10</td></tr>\n",
       "</table>"
      ]
     },
     "output_type": "execute_result",
     "metadata": {}
    },
    {
     "data": {
      "text/plain": [
       ""
      ]
     },
     "execution_count": 9,
     "output_type": "execute_result",
     "metadata": {}
    }
   ],
   "source": [
    "res[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    ""
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2.0
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}